Access to Mental Health and Substance Use Treatment in Comprehensive Primary Care Plus

This cohort study examines whether participation in the Centers for Medicare & Medicaid Services’ Comprehensive Primary Care Plus model was associated with improved access to mental health and substance use treatment.


eMethods. Inverse Probability Score Weighting Approach: Probit Regression Results and Distribution of Propensity Scores Across Study Groups
To enroll in CPC+, primary care practices had to meet certain requirements.Chiefly, practices were required to serve a minimum of 150 Medicare fee-for-service beneficiaries, pass a Centers for Medicare & Medicaid Services (CMS) program integrity screening, and have certified health information technology practices in place, including use of electronic health records and Electronic Clinical Quality Measures.Some practices that met these requirements still chose not to enroll in CPC+.As a result of both enrollment requirements and self-selection into the program, CPC+ practices can look inherently different from other practices across numerous dimensions.
A valid comparison of CPC+ practices to non-CPC+ practices must account for the baseline differences in practice characteristics, which may affect the outcomes examined in our study.In our analysis, we employed an Inverse Probability Weighting (IPW) methodology to balance our sample.
We first estimate the probability of a practice being a CPC+ practice using a probit regression: 1[+  ] =  0 +  1 ℎ  +  2 ℎ 2 +  3  +  4  2 +  5  +  6  2 +  7  +  8  2 +  9  +  10  2 +  11  +  12  2 + Where we control for both the linear and quadratic terms of: (a) the number of physicians operating in the practice; (b) the number of patients attributed to the practice; (c) the average age of patients in the practice; (d) the share of male patients in the practice; (e) the share of Medicare Advantage patients in the practice; and (f) the share of HMO patients in the practice.Regression results are reported in eMethods Table 1.The model is moderately to highly successful in predicting CPC+ enrollment, with a model pseudo R-squared of 0.579.
We use the predicted probabilities of our probit model to construct inverse-probability weights.eMethods Table 2 reports on the covariate balance in the raw sample and in our sample following inverse-probability weighting.Columns (1) and (3) report the mean difference in the standardized variables in the raw sample and the inverseprobability weighted sample, respectively.Columns (2) and (4) report the p-value of the corresponding standardized difference for each sample.In the raw sample, we find a statistically significant difference in means across all reported practice characteristics.After weighting, only three practice characteristics exhibit a mean difference that is statistically significant at the 95% level: the percent of practice members with hypertension, diabetes, and anxiety disorders.
Finally, eMethods Figure 1 plots the predicted propensity score from our probit regression, restricted to our trimmed sample (omitting the bottom and top 5% of the sample in terms of inverse-probability weights).Compared to the raw sample, the distribution of CPC+ practices and non-CPC+ practices track more closely in the inverseprobability weighted sample.

Variable Coefficient
Number We tested for pre-treatment parallel trends by limiting the sample to the pre-treatment period (2018 to 2019) and tested the significance of the interaction between the treatment variable and the linear quarter dummies (i.e., treat*Qx.YEAR).A non-significant p-value indicates that the pretreatment trends are parallel.

National Drug Codes (NDCs) for Antidepressants From the US Food & Drug Administration NDC Directory Note:
NDCs available upon request.There were 1,774 unique NDC codes.

National Drug Codes (NDCs) for Anxiolytics and Sedative-Hypnotics From the US Food & Drug Administration NDC Directory Note:
NDCs available upon request.There were 1,221 unique NDC codes.

Baseline Trends Test (Parallel Trends Test): Primary Study Outcomes for Patients Diagnosed With Anxiety or Depression
To get the final study sample, the raw sample (i.e., all primary care practices) was trimmed by omitting the bottom and top 5% of the sample in terms of inverseprobability weights.The raw sample had a total of 3,853 practices (173 CPC+ and 3,680 non-CPC+).The trimmed sample (i.e., final study sample) had a total of 469 practices (152 CPC+ and 317 non-CPC+).

01, * p<0.05 Psych Hosp: psychiatric hospitalization Comm MH Ctr Visits: community mental health center visits Subst Use Treat: substance use treatment Antidep: antidepressant Bupre: buprenorphine We
tested for pre-treatment parallel trends by limiting the sample to the pre-treatment period (2018 to 2019) and tested the significance of the interaction between the treatment variable and the linear quarter dummies (i.e., treat*Qx.YEAR).A non-significant p-value indicates that the pretreatment trends are parallel.

Baseline Trends Test (Parallel Trends Test): Primary Study Outcomes for Patients Diagnosed with Opioid Use Disorder
** p<0.